| Faculty | Faculty of Science (FPR) | ||||
|---|---|---|---|---|---|
| Study programme | Artificial Intelligence and Data Science (N0619P140001) | ||||
| Branch of study / Specialization | Artificial Intelligence and Data Science (N0619P140001/0 - 2025) | ||||
| Level of acquired qualification | Postgraduate Master | ||||
| Form of study | Full-time | ||||
| Standard length of study | 2 years | ||||
| Number of ECTS credits | 120 | ||||
| Qualification awarded | Master (7) | ||||
| Access to further studies | Doctoral study programme | ||||
| Type of completion | State Final Exam | ||||
| Study and Examination Code | URL | ||||
| Faculty coordinator for international students |
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| Key learning outcomes | Graduates of the cross-border joint study programme MAID will acquire knowledge, skills and competences in the specialised field of applied informatics ? artificial intelligence (machine learning, analysis and prediction methods) and data science (data mining, data analysis or big data processing). | ||||
| Specific admission requirements | unspecified | ||||
| Specific provisions for recognition of prior learning | unspecified | ||||
| Qualification requirements and regulations | unspecified | ||||
| Profile of the programme | unspecified | ||||
| Persistence requirements | unspecified | ||||
| Occupational profiles of graduates with examples | unspecified | ||||
| Branch of study / Specialization guarantor | unspecified |
| Course code | Course title | credits | Completion | Time requirements | Recommended year of study | Recommended semester | Course availability |
|---|---|---|---|---|---|---|---|
| UAI/521 | Feature Engineering for Data Science | 4 | Zk+ | 2+1+8S | 1 | Winter | |
| FPR/913E | Training in OSH, FS and Cybersecurity | 0 | Zp | 8S+0+0 | 1 | Winter | |
| UAI/501 | Math for Artificial Intelligence and Dat | 6 | Zk+ | 2+2+0 | 1 | Winter | The course is available to visiting students |
| UAI/500 | Information Theory | 4 | Zk | 2+1+0 | 1 | Winter | The course is available to visiting students |
| FPR/914 | Courses Evaluation | 0 | Zp | 0+0+0 | 1 | Winter | |
| UAI/502 | Computational Intelligence | 4 | Zk | 1+2+0 | 1 | Winter | The course is available to visiting students |
| UAI/504 | Advanced data storages and analyses | 6 | Zk+ | 2+2+0 | 1 | Winter | The course is available to visiting students |
| UFY/505 | Parallel programming and computing | 4 | Zk+ | 1+2+0 | 1 | Winter | The course is available to visiting students |
| FPR/914 | Courses Evaluation | 0 | Zp | 0+0+0 | 1 | Summer | |
| UAI/506 | Internship | 20 | Zp | 0+480S+10S | 2 | Winter | |
| FPR/914 | Courses Evaluation | 0 | Zp | 0+0+0 | 2 | Winter | |
| UAI/882 | Master Thesis, Practical Part | 20 | Zp | 0+15+0 | 2 | Summer | |
| FPR/914 | Courses Evaluation | 0 | Zp | 0+0+0 | 2 | Summer | |
| UAI/507 | Advanced Topics in AI (Lab) | 5 | Zp | 0+0+150S | 2 | Summer | The course is available to visiting students |
| UAI/508 | Master Seminar | 5 | Zp | 0+0+50S | 2 | Summer |
| Course code | Course title | credits | Completion | Time requirements | Recommended year of study | Recommended semester | Course availability |
|---|---|---|---|---|---|---|---|
| UAI/SN21 | Theoretical Fundamentals | 0 | Szv | 0+0+0 | - | - | |
| UAI/SN23 | Data Science | 0 | Szv | 0+0+0 | - | - | |
| UAI/SN22 | Artificial Intelligence | 0 | Szv | 0+0+0 | - | - |
| Course code | Course title | credits | Completion | Time requirements | Recommended year of study | Recommended semester | Course availability |
|---|---|---|---|---|---|---|---|
| OJZ/550 | Czech for foreigners beginners | 2 | Zp | 0+2+0 | - | - | The course is available to visiting students |
| OJZ/721 | German I | 2 | Zk | 0+2+0 | - | Winter | The course is available to visiting students |
| OJZ/722 | German II. | 2 | Zk | 0+2+0 | - | Summer | The course is available to visiting students |